Welcome to the world of FunASR – a powerful toolkit designed for speech recognition! FunASR aims to connect academic research with practical industrial applications in a user-friendly manner. Whether you’re a researcher or developer, this guide will help you embark on your journey to implementing efficient speech recognition models.

What is FunASR?

FunASR is a comprehensive speech recognition toolkit that offers various features such as automatic speech recognition (ASR), voice activity detection (VAD), and more. It provides easily accessible scripts and tutorials that can help you fine-tune and deploy industrial-grade speech recognition models.

Key Highlights of FunASR

• Supports an array of functionalities including ASR, VAD, punctuation restoration, and speaker verification.
• Open-sourced collection of pre-trained models available on ModelScope and Hugging Face.
• The Paraformer-large model is non-autoregressive, boasting high accuracy and efficient deployment capabilities.

Installation

To get started with FunASR, follow these installation steps:

• For the simplest installation, use the command:

pip3 install -U funasr

• Alternatively, install from source code:

git clone https://github.com/alibaba/FunASR.git
cd FunASR
pip3 install -e .

• Optionally, install ModelScope for pre-trained models:

pip3 install -U modelscope

Quick Start Guide

Now that you have installed FunASR, let’s get you started with some quick examples. You can test your audio files with the following commands:

Speech Recognition (Non-Streaming)

Use the following code snippet to perform speech recognition on an audio file:

from funasr import AutoModel
model = AutoModel(model="paraformer-zh", model_revision="v2.0.4")
res = model.generate(input="example_asr_example.wav")
print(res)

Speech Recognition (Streaming)

For real-time recognition, you can adapt the following code:

from funasr import AutoModel
model = AutoModel(model="paraformer-zh-streaming", model_revision="v2.0.4")
# Process chunks of audio...

This works similarly to how you would stream a live video, processing smaller segments of audio in near real-time.

Voice Activity Detection (VAD)

To implement voice activity detection, run this command:

from funasr import AutoModel
model = AutoModel(model="fsmn-vad", model_revision="v2.0.4")
res = model.generate(input="example_asr_example.wav")
print(res)

Troubleshooting Tips

If you encounter issues while setting up or using FunASR, here are some troubleshooting tips:

• Ensure all dependencies are installed correctly.
• Check your Python version; FunASR works best with Python 3.6 and above.
• For model-related errors, verify that you are using the correct model paths and versions.
• If audio files are not recognized properly, ensure they are in the correct format and quality. Using sample files provided by FunASR can be beneficial.

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Conclusion

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.